Computational Systems Analysis of Dopamine Metabolism
 

(full text of this article is available via link)

http://www.plosone.org/article/info%...l.pone.0002444
Research Article


Computational Systems Analysis of Dopamine Metabolism
Zhen Qi1,2,3, Gary W. Miller2,3, Eberhard O. Voit1*

1 Department of Biomedical Engineering, Georgia Institute of Technology and Emory University Medical School, Atlanta, Georgia, United States of America2 Department of Environmental and Occupational Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America3 Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, Georgia, United States of America

Abstract
A prominent feature of Parkinson's disease (PD) is the loss of dopamine in the striatum, and many therapeutic interventions for the disease are aimed at restoring dopamine signaling. Dopamine signaling includes the synthesis, storage, release, and recycling of dopamine in the presynaptic terminal and activation of pre- and post-synaptic receptors and various downstream signaling cascades. As an aid that might facilitate our understanding of dopamine dynamics in the pathogenesis and treatment in PD, we have begun to merge currently available information and expert knowledge regarding presynaptic dopamine homeostasis into a computational model, following the guidelines of biochemical systems theory. After subjecting our model to mathematical diagnosis and analysis, we made direct comparisons between model predictions and experimental observations and found that the model exhibited a high degree of predictive capacity with respect to genetic and pharmacological changes in gene expression or function. Our results suggest potential approaches to restoring the dopamine imbalance and the associated generation of oxidative stress. While the proposed model of dopamine metabolism is preliminary, future extensions and refinements may eventually serve as an in silico platform for prescreening potential therapeutics, identifying immediate side effects, screening for biomarkers, and assessing the impact of risk factors of the disease.

I couldn't stick it out Madelyn, although I know it's sooo interesting. Mutually understandable language should be another step in the process. If they [researchers, biotech CEOs...government, etc, ] say they understand it - they should be able to communicate what this means without all the greedy - and that words applies here - and deceptive marketing and code deciphering required to interpret the results, followed by statistics and stocks involved.

There is such a trickle down effect that it sure looked like a recent announcement about Azilect was not completely about making people get better. Is the stock market ready to commit with the newer research models? That's a question I have. Anyone?

This claim about Azilect prompted at least 3 quick disclaimers - from PAN - MJFF - and PDF. If there are more that I didn't see- that's even stronger....

There had been a request from Amy Rick PAN CEO of the researchers at the UDALL centers to send a version of their results in understandable language. I wonder if any of the centers actually sent one.

Translator if there is one please ?

Is this something similar?
 

But not PD specific....math seems like the next best thing to time travel, which treatments are going to have to do to catch up with knowledge.
Pitt Team Receives $2.5 Million to Simulate and Analyze Brain, Immune System Activity and Apply Math to Medical Problems

Models of how systems evolve and function under certain conditions could lead to better medical understanding of when and how to treat patients

PITTSBURGH-In an effort to promote the application of mathematics to medical treatment, researchers in the University of Pittsburgh's Department of Mathematics will undertake a $2.5 million project to create models of how the brain and immune system function and change over time in response to certain illnesses, infections, and treatment. The models are intended to help doctors better understand and predict the possible short- and long-term responses of their patient's body to treatment.

The National Science Foundation awarded University professor G. Bard Ermentrout, assistant professor Beatrice Riviere, associate professor Jonathan Rubin, assistant professor David Swigon, and professor and interim chair Ivan Yotov a nearly $1.8 million Research Training Group (RTG) award. The RTG includes resources for creating training programs for mathematics students wherein they would work with physicians and biologists to help resolve complicated medical problems through mathematics. Pitt's School of Arts and Sciences-which houses the mathematics department-provided additional funds.

The team will create a variety of computer models based on differential equations-which predict how systems evolve over time-with the medical guidance of scientists and doctors in Pitt's Departments of Biological Sciences and Neuroscience, the Pitt School of Medicine, and UPMC, said Rubin, a coinvestigator on the project.

http://mac10.umc.pitt.edu/m/FMPro?-d...&id=3369&-Find